How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds-Reference-Cited by-同舟云学术

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How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds

Published:2019-05 Issue: Volume:77 Page:70-78
ISSN:0966-6923
Container-title:Journal of Transport Geography
language:en
Short-container-title:Journal of Transport Geography

Author:

Ding Chuan^ORCID,Cao Xinyu^ORCID,Liu Chao

Funder

National Natural Science Foundation of China

China Association for Science and Technology

Publisher

Elsevier BV

Subject

General Environmental Science,Transportation,Geography, Planning and Development

Reference41 articles.

1. Examining the effect of the Hiawatha LRT on auto use in the twin cities;Cao;Transp. Policy,2018

2. Application of geographically weighted regression to the direct forecasting of transit ridership at station-level;Cardozo;Appl. Geogr.,2012

3. Alternative approaches to modeling the travel-demand impacts of smart growth;Cervero;J. Am. Plan. Assoc.,2006

4. Transit-Oriented Development in the United States: Experiences, Challenges, and Prospects;Cervero,2004

5. Direct ridership model of bus rapid transit in Los Angeles County, California;Cervero;Transp. Res. Rec. J. Transp. Res. Board,2010

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4. A CNN-LSTM Model for Short-Term Passenger Flow Forecast Considering the Built Environment in Urban Rail Transit Stations;Journal of Transportation Engineering, Part A: Systems;2024-11

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